Dynamic Inversion Research Articles

Promoting the Maneuverability and Fault-Tolerant Control Capabilities of Dual-System/Hybrid VTOL UAVs

This paper presents an active fault-tolerant flight control system (FCS) design for the dual-system/hybrid VTOL UAV configuration that maximally exploits its inherent over-actuation abilities to provide higher levels of fault-tolerance and reliability compared to that of the other VTOL UAVs configurations up to this point. The significance of this study is to convert the main drawback of having the vertical rotors as dead weights during the cruise to a key advantage where all the UAV's controls are kept active during all the flight phases raising the UAV's fault-tolerance and maneuverability abilities. The FCS proposed elaborates on a new architecture for the hierarchical automatic control loops using the dynamic inversion control to design the trajectory tracking virtual commands and employing optimal dynamic control allocation to optimally resolve the controls redundancy. Regarding fault-tolerance, the presented FCS handles simultaneous failures and jamming of all the control surfaces during flight where the control commands to the healthy controls (vertical rotors) were automatically adapted such that the trimming and trajectory tracking were successfully maintained till the mission end. Additionally, this paper addresses for the first time the employment of the controls redundancy to enhance the VTOL UAV's maneuverability in fault-free cases, where we present a study of reducing the minimum turn radius of the UAV when the vertical rotors are employed with the control surfaces during the maneuver. A reduction of 38% in the coordinated steady-level minimum turn radius turn at 35 m/sec flight speed was achieved.

Research on integrated aircraft-engine control method of hypersonic vehicle based on dynamic inversion control

In order to reduce the influence of the coupling characteristics between the aircraft and engine of hypersonic vehicle, an integrated aircraft-engine control method of hypersonic vehicle is studied in this paper. Firstly, the control-oriented aircraft-engine integrated mathematical model of the hypersonic vehicle is established. Then, by using the nonlinear dynamic inversion (NDI) and the incremental nonlinear dynamic inversion (INDI), the outer loop control algorithm with slow attitude change and the inner loop control algorithm with fast angular rate change are respectively designed. Moreover, based on the online ontology model including aircraft-engine coupling characteristics of the hypersonic vehicle, the coupling control scheme of flight posture and engine of the hypersonic vehicle is designed in the form of control linkage. Finally, the reference model, error control, online estimation and other modules are introduced into the NDI controller to ensure the flight quality and robustness requirements of the hypersonic vehicle. The simulation results show that the aircraft-engine coupling control scheme based on the NDI achieves the expected control performance.

Nonlinear Control Allocation Using a Piecewise Multilinear Representation

Nonlinear control allocation is an important part of modern nonlinear dynamic inversion based flight control systems which require a highly accurate model of aircraft aerodynamics. Generally, an accurately implemented onboard model determines how well the system nonlinearities can be canceled. Thus, a more accurate model results in better cancellation, leading to higher performance of the controller. In this paper, a control system is presented that combines nonlinear dynamic inversion with a piecewise multilinear representation based control allocation. The piecewise multilinear representation is developed through a generalization of the Kronecker product for block matrices, combined with the canonical piecewise linear representation of nonlinear functions. Analytical expressions for the Jacobian of the piecewise multilinear model are also presented. The proposed formulation gives an equivalent analytical representation of piecewise multilinear aerodynamic data and thus is capable of accurately modeling nonlinear aerodynamics over the entire flight envelope of an aircraft. The resulting nonlinear controller is applied to control a tailless flying wing aircraft with ten independently operating control surfaces. The simulation results for two innovative control surface configurations indicate that an accurate control allocation performance can be achieved, leading to better tracking performance compared with the control allocation methods based on multivariate polynomials and splines.

L1 Adaptive Control Based on Dynamic Inversion for Morphing Aircraft

Morphing aircraft are able to keep optimal performance in diverse flight conditions. However, the change in geometry always leads to challenges in the design of flight controllers. In this paper, a new method for designing a flight controller for variable-sweep morphing aircraft is presented—dynamic inversion combined with L1 adaptive control. Firstly, the dynamics of the vehicle is analyzed and a six degrees of freedom (6DOF) nonlinear dynamics model based on multibody dynamics theory is established. Secondly, nonlinear dynamic inversion (NDI) and incremental nonlinear dynamic inversion (INDI) are then employed to realize decoupling control. Thirdly, linear quadratic regulator (LQR) technique and L1 adaptive control are adopted to design the adaptive controller in order to improve robustness to uncertainties and ensure the control accuracy. Finally, extensive simulation experiments are performed, wherein the demonstrated results indicate that the proposed method overcomes the drawbacks of conventional methods and realizes an improvement in control performance.

DIW-based reflection full waveform inversion and its application of land seismic data

Abstract The exploration zone in Northwest China poses unique challenges due to its complex structures, fractured blocks, deep reservoirs, and geological anomalies. Conventional velocity modeling and migration imaging methods face difficulties in accurately imaging the underlying reservoirs beneath abnormal rock formations, resulting in poor signal-to-noise ratio and resolution. Moreover, the seismic data quality often falls short, leading to unfocused images. To address these challenges, we propose a novel approach: dynamic image warping-based reflection full waveform inversion. This method combines a model regularization strategy and structural constraints to generate high-resolution velocity models. The application in the Taha Industrial Zone demonstrates that the proposed method effectively characterizes the velocity characteristics of special geological bodies, such as deep weathering crusts, improving imaging effects and resolution, which allows for a more precise understanding of the complex geological features.

Time-Scale Separation Control for a Class of Current Distribution Strategy in AMBs-Rotor System With Bounded Bus Voltage

In active magnetic bearings (AMBs) systems, good dynamic characteristics and low power consumption are two important concerns, which are difficult to be obtained simultaneously if considering bounded bus voltage. This paper proposes a universal current distribution constraint format and a related time-scale separation control scheme to achieve improvements in both aspects. Considering the bounded bus voltage and symmetrical configuration in one AMB control axis, a double-input three-order nonlinear model is established to describe the AMBs-rotor system. Subsequently, a constraint format is propounded to cover and improve existing current distribution strategies. The power consumption and voltage response are compared between different instances under this constraint format. Then, the double-input model is converted to a single-input cascaded nonlinear system, and a time-scale separation control scheme is designed accordingly. The scheme contains a nominal controller and a dynamic inversion. The nominal controller determines the dynamic characteristics of the AMBs-rotor system. The dynamic inversion compensates for the nonlinearity of the system based on the characteristics of the amplifier. This scheme can preserve the closed-loop stability by only adjusting the time-scale coefficient. Finally, experimental results demonstrate the advantages of the proposed method in aspects of dynamic performance, voltage response, and power consumption.

Spacecraft attitude control based on generalised dynamic inversion with adaptive neural network

AbstractThis paper proposes a robust generalised dynamic inversion (GDI) control system design with adaptive neural network (NN) estimation for spacecraft attitude tracking under the absence of knowledge of the spacecraft inertia parameters. The robust GDI control system works to enforce attitude tracking, and the adaptive NN augmentation compensates for the lack of knowledge of the spacecraft inertia parameters. The baseline GDI control law consists of a particular part and an auxiliary part. The particular part of the GDI control law works to realise a desired attitude dynamics of the spacecraft, and the auxiliary part works for finite-time stabilisation of the spacecraft angular velocity. Robustness against modeling uncertainties and external disturbances is provided by augmenting a siding mode control element within the particular part of the GDI control law. The singularity that accompanies GDI control is avoided by modifying the Moore-Penrose generalised inverse by means of a dynamic scaling factor. The NN weighting matrices are updated adaptively through a control Lyapunov function. A detailed stability analysis shows that the closed loop system is semi-global practically stable. For performance assessment, a spacecraft model is developed, and GDI-NN control is investigated for its attitude control problem through numerical simulations. Simulation results reveal the efficacy, robustness and adaptive attributes of proposed GDI-NN control for its application to spacecraft attitude control.

Dissolved Oxygen Inversion Based on Himawari-8 Imagery and Machine Learning: A Case Study of Lake Chaohu

Dissolved oxygen (DO) concentration is a widely used and effective indicator for assessing water quality and pollution in aquatic environments. Continuous and large-scale inversion of water environments using remote sensing imagery has become a hot topic in water environmental research. Remote sensing technology has been extensively applied in water quality monitoring, but its limited sampling frequency necessitates the development of a high-frequency dynamic water quality monitoring model. In this study, we utilized Lake Chaohu as a case study. Firstly, we constructed a dynamic water quality inversion model for monitoring DO concentrations using machine learning methods, with Himawari-8 (H8) satellite imagery as input data and DO concentrations in Lake Chaohu as output data. Secondly, the developed DO concentration inversion model was employed to estimate the overall grid-based DO concentration in the Lake Chaohu region for the years 2019 to 2021. Lastly, Pearson correlation analysis and significance tests were performed to examine the correlation and significance between the estimated grid-based DO concentration and the ERA5 reanalysis dataset. The results demonstrate that the Random Forest (RF) model performs best in DO concentration inversion, with a high R2 score of 0.84, and low RMSE and MAE values of 0.69 and 0.54, respectively. Compared to other models, the RF model improves average performance with a 38% increase in R2, 13% decrease in RMSE, and 33% decrease in MAE. The model accurately predicts DO concentrations. Furthermore, the inversion results reveal seasonal differences in DO concentrations in Lake Chaohu from 2019 to 2021, with higher concentrations in spring and winter, and lower concentrations in summer and autumn. The average DO concentrations in the northwest, central-south, and northeast regions of Lake Chaohu are 10.12 mg/L, 9.98 mg/L, and 9.96 mg/L, respectively, with higher concentrations in the northwest region. Pearson correlation analysis indicates a significant correlation (p < 0.01) between DO concentrations and temperature, surface pressure, latent heat flux from the atmosphere to the surface, and latent heat flux from the surface to the atmosphere, with correlation coefficients of −0.615, 0.583, −0.480, and 0.444, respectively. The results verify the feasibility of using synchronous satellites for real-time inversion of DO concentrations, providing a more efficient, economical, and accurate means for real-time monitoring of DO concentrations. This study has practical value in improving the efficiency and accuracy of water environmental monitoring.

Asymmetric Bipartite Consensus of Nonlinear Agents with Communication Noise

In this paper, the asymmetric bipartite consensus problem of a nonlinear multi-agent system is solved using Distributed Nonlinear Dynamic Inversion (DNDI) based controller. The application of DNDI is new in the context of asymmetric bipartite consensus, and it inherits all the advantages of NDI and works efficiently to solve the asymmetric bipartite problem. The mathematical details presented provide theoretical proof of its efficiency. A realistic simulation study is performed to establish the claims. The controller’s performance has been tested in the presence of communication noise, and the results are promising.

Electric Flight in Extreme and Uncertain Urban Environments

In a typical application scenario for electric aircraft, the emerging urban air mobility is faced with uncertain environmental conditions. To investigate the potential influence of uncertainties, this paper first develops comprehensive models of aircraft rigid body motion and electric propulsive performance. The urban environment model is built with emphasis on wind speed and the heat island effect. Thereafter, a flight guidance law augmented with nonlinear dynamic inversion is proposed to facilitate the performance evaluation of electric aircraft. Multiple simulations at various dates, times, and with different battery aging statuses are conducted. The results show that the battery aging effect and ambient temperature change are the most important factors that influence the aircraft performance. Suggestions to enhance the performance are given based on simulations.

Pilot Command Implementation in Aircrafts: A New Approach Based on Dynamic Inversion

A new approach based on dynamic inversion is proposed in this paper for implementing pilot commands in an aircrafts. The command inputs from the pilot are assumed to be (i) the normal acceleration and forward velocity commands in the longitudinal mode and (ii) roll rate, height and forward velocity commands in the lateral mode. A major difference here is that the second derivatives of the velocities along body y and z directions are assumed to be zero, as opposed to the first derivatives (which is used in many published literature). The new approach leads to a significant reduction of tuning parameters in the control design process, which is a major advantage. Detailed derivations of the modified approach are presented with respect to the generic aircraft dynamics model available in [16]. Extensive Six-DOF simulation studies show that, besides the above advantage, the new approach leads to two other additional advantages; namely reduced oscillatory response and reduced control magnitude. In a comparison study with an existing method using the Six-DOF model for Boeing 747 (with the numerical data available in [16]), numerical results clearly show the improved performance of this new approach. Furthermore, in lateral mode a technique for obtaining a corresponding roll rate command from the desired bank angle command is also implemented. Comparison results show improved performance of the new approach with this modification as well.

Alignment and Dynamic Inversion of Planar Chirality in Pillar[n]arenes.

Pillar[n]arenes are symmetrical macrocyclic compounds composed of benzene panels with para-methylene linkages. Each panel usually exhibits planar chirality and prefers chirality-aligned states. Because of this feature, pillar[n]arenes are attractive scaffolds for chiroptical materials that are easy to prepare and optically resolve and show intense circular dichroism (CD) signals. In addition, rotation of the panels endows the chirality of pillar[n]arenes with a dynamic nature. The chirality in tubular oligomers and supramolecular assemblies sometimes show time- and procedure-dependent alignment phenomena. Furthermore, the CD signals of some pillar[n]arenes respond to the addition of chiral guests when their dynamic chirality is coupled with host-guest properties. By using diastereomeric pillar[n]arenes with additional chiral structures, the response can also be caused by achiral guests and changes of the environment, providing molecular sensors.

Alignment and Dynamic Inversion of Planar Chirality in Pillar[n]arenes

AbstractPillar[n]arenes are symmetrical macrocyclic compounds composed of benzene panels with para‐methylene linkages. Each panel usually exhibits planar chirality and prefers chirality‐aligned states. Because of this feature, pillar[n]arenes are attractive scaffolds for chiroptical materials that are easy to prepare and optically resolve and show intense circular dichroism (CD) signals. In addition, rotation of the panels endows the chirality of pillar[n]arenes with a dynamic nature. The chirality in tubular oligomers and supramolecular assemblies sometimes show time‐ and procedure‐dependent alignment phenomena. Furthermore, the CD signals of some pillar[n]arenes respond to the addition of chiral guests when their dynamic chirality is coupled with host–guest properties. By using diastereomeric pillar[n]arenes with additional chiral structures, the response can also be caused by achiral guests and changes of the environment, providing molecular sensors.

Integrated Controller for Divert Thruster Flight Propulsion Control Systems

Future generation missile calls for development of fast response propulsion based control systems to achieve hit-to-kill miss distance against highly manoeuvrable targets covering high-endo to exo-atmosphere regions. Control systems based on solid propulsion are developed connecting multiple pintle nozzles and control thrust vector is generated with distribution hot gasses in pitch/yaw directions. Differential distribution of hot gasses among multiple nozzles is complex due to time varying coupled non-linear chamber pressure dynamics with propellant combustion and nozzles’ flow phenomena and methods based on linear control may not ensure stability in wide operating conditions. There is need to develop "Unified Controller" based on non-linear formulation to ensure control stability in wide operating conditions of various mission applications, with advanced features for new generation missiles to counter various futuristic targets, and achieve hit-to-kill capabilities following integrated approach in order to improve the total system performance. Non-linear algorithms proposed in the recent literature do not exploit synergism between plant and actuation systems dynamics. Present paper presents novel non-linear feedback linearization technique, Dynamic Inversion, a relatively straightforward approach in Integrated Control Framework (ICF) implementing inherent time scale separation between solid motor plant and hot gas flow control valve actuation system. To ensure stability in various operating conditions and assure robust performance in the presence of parameter inaccuracies, controller is augmented with model-following neuro-adaptive design. Prototype systems: Thrust Controlled Motor (TCM) and Divert Thruster Flight Propulsion Control Systems (DTFPCS) are developed to demostrate/validate "Unified Controller" for missile control system. Closed loop control of chamber pressure is demonstrated with single pintle nozzle system and control thrust vector generation with multiple nozzle systems. Model update takes place adaptively online and unlike a typical indirect adaptive control approach, there is no need to update the individual parameters explicitly. Instead the inaccuracy in the system output dynamics is captured directly and then used in modifying the control. Based on present work, missilecontrol systems for various applications can be developed with limited controller changes and thereby minimizing number of developmental tests and cost.

Gliding Vehicle Controller Based on Neural Network Compensating Dynamic Inversion Error

Aiming at the attitude control problem of the gliding vehicle with uncertainty and strong coupling, a dynamic inversion control method based on RBF neural network compensated inversion error is discussed. Firstly, based on the double time scale separation hypothesis, the controlled aircraft model is divided into a fast and slow state subsystem. Then the dynamic inversion control laws are designed for each of the two subsystems. The weight update rule of the RBF neural network is derived online based on the Lyapunov stability principle to compensate for the inversion error caused by the modeling error and uncertainty. The simulation verifies the effectiveness of the control law. The robustness of the control system after neural network compensation is significantly improved.

Bayesian inference of polymerase dynamics over the exclusion process.

Transcription is a complex phenomenon that permits the conversion of genetic information into phenotype by means of an enzyme called RNA polymerase, which erratically moves along and scans the DNA template. We perform Bayesian inference over a paradigmatic mechanistic model of non-equilibrium statistical physics, i.e. the asymmetric exclusion processes in the hydrodynamic limit, assuming a Gaussian process prior for the polymerase progression rate as a latent variable. Our framework allows us to infer the speed of polymerases during transcription given their spatial distribution, while avoiding the explicit inversion of the system's dynamics. The results, which show processing rates strongly varying with genomic position and minor role of traffic-like congestion, may have strong implications for the understanding of gene expression.

Robust Stability and Performance Analysis of Incremental Dynamic-Inversion-Based Flight Control Laws

Incremental nonlinear dynamic inversion (INDI) is a sensor-based control law design strategy that is based on the principles of feedback linearization. Contrary to its nonincremental counterpart (nonlinear dynamic inversion), this design method does not require a complete onboard model of the airframe dynamics and is therefore more robust against regular perturbations arising from aerodynamic variations. Therefore, INDI brings a natural design approach to desirable flying qualities. However, robustness against singular perturbations, which may arise due to transport delays, elastic airframe effects, or other types of badly modeled or unknown dynamics, is a known challenge for INDI-based control laws. Therefore, this paper addresses the question of robust stability and performance for INDI and its linear form (incremental dynamic inversion [IDI]) in the context of mixed regular and singular perturbations. This is done through analytical insights and by performing quantitative robustness assessments based on the structured singular value framework. Additionally, inversion loop augmentation solutions are investigated using robust synthesis techniques to improve the robustness characteristics of basic IDI designs.

Model-Free Sliding Mode Enhanced Proportional, Integral, and Derivative (SMPID) Control

This study proposes a type of Sliding Mode-based Proportional, Integral, and Derivative (SMPID) controllers to establish a model-free (treat dynamic plants as a whole uncertainty) sliding model control (MFSMC) platform for Bounded-Input and Bounded-Output (BIBO) dynamic systems. The SMPID design (1) proposes a sliding mode error (rather than error) as the PID input, (2) directly links to Lyapunov asymptotic stability to provide total robust nonlinear dynamic inversion (NDI), and (3) reduces the chattering effects in terms of Lyapunov definite positive stability. Further, the study proposes a general SMC framework to accommodate asymptotic time stabilisation and finite-time stabilisation for both model-based and model-free designs. A U-control framework is presented to integrate the SMPID control (for NDI) and an invariant control (IC) (for specifying the whole control system’s dynamic and static responses), which significantly relaxes the PID tunings and generates the specified performance. To provide assurance and guidance for applications and expansions, this study presents the relevant fundamental analyses and transparent simulated bench tests. It should be noted that the new SMPID in forms of u=SMPID(σ(e))=PID(sliding-mode) is different from that studied u=sliding-mode(PID(e)) in expression and functionality.

Discrete-Time Incremental Backstepping Control with Extended Kalman Filter for UAVs

In this study, a discrete-time incremental backstepping (DTIBS) controller with an extended Kalman filter (EKF) is proposed for unmanned aerial vehicles (UAVs) with unknown actuator dynamics. The Taylor series and an approximate discrete method are employed, transforming the second-order continuous-time nonlinear system into a discrete-time nonlinear plant with an incremental input form. The incremental control laws are designed using the incremental nonlinear dynamic inversion (INDI) method and the time-delay control (TDC) method. The TDC is introduced to design the control law, eliminating the need for prior knowledge of the control effectiveness matrix involving some unknown aerodynamic coefficients. In addition, the airflow angle and body rotation rate are selected as key system states, and the EKF is used to design a state estimator to estimate the local state of the small unmanned aerial vehicle closed-loop flight control system under strong noise conditions. The effectiveness of the DTIBS control method with EKF is verified through numerical simulation. The results show that the proposed method can effectively estimate the state under the typical noise characteristics of low-cost sensors, and the closed-loop control systems has good tracking performance and can quickly and effectively track sudden commands.

Dynamic Inversion Model of the Mooring Force on a Floating Bollard of a Sea Lock

Sea locks that connect inland canals and rivers to the open sea are crucial links that ensure the efficient navigation of ships. Floating bollards (FBs) are significant components of sea locks, and they are affected by factors such as large ships, speed of entry, and irregular mooring lines coupled with corrosion by chloride salts from seawater intrusion from the environment. These factors aggravate damage to metal structures, which seriously threatens the safety of FBs. Overloading of FBs by mooring forces caused by the illegal use of FBs for the braking of large ships that enter locks at excessive speed is the main cause of structural damage and overload failure for FBs. Controlling the dynamic mooring force acting on the FB is an important prerequisite to ensure the safe passage of a ship through a lock. It is impossible to perform real-time monitoring of the magnitude and direction of the mooring force on an FB by installing load-measuring equipment on the mooring line. Therefore, in this study, the structure of an FB in a sea lock project was taken as an example, and the mathematical relationships between the strain in the load-sensitive area of the FB and the mooring force and the mooring angle were quantified. A dynamic inversion model of the ship mooring force on an FB was proposed. This model used real-time feedback from the strain signal in the load-sensitive region of the FB structure to obtain information about the mooring force. The accuracy of the model was verified by conducting tests with a physical model of the topside structure of the FB and comparing the predicted results with the test data. The research results can lay a theoretical foundation for real-time monitoring of the structural response of an FB under the action of mooring forces and promote the development of intelligent methods for the operation and maintenance of a sea lock, which have important scientific significance and engineering value.